J
Javad Roostaei
Researcher at University of North Carolina at Chapel Hill
Publications - 14
Citations - 317
Javad Roostaei is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 6, co-authored 10 publications receiving 139 citations. Previous affiliations of Javad Roostaei include Indiana University & Wayne State University.
Papers
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Mixotrophic Microalgae Biofilm: A Novel Algae Cultivation Strategy for Improved Productivity and Cost-efficiency of Biofuel Feedstock Production.
TL;DR: This work proved that microalgae biofilms under mixotrophic condition exhibited significantly higher productivity and quality of biofuel feedstock, and demonstrated the applicability of integrating this novel cultivation method with wastewater for maximum efficiency.
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Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance
TL;DR: In this article, the authors evaluated the effect of seven different feature selection methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP influent flow.
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Spatially Explicit Life Cycle Assessment: Opportunities and challenges of wastewater-based algal biofuels in the United States
Javad Roostaei,Yongli Zhang +1 more
TL;DR: In this paper, a spatially-explicit high resolution life cycle assessment (SEHR-LCA) model for wastewater-based algal biofuel production, by integrating GIS analysis, and site-specific wastewater Treatment Plants (WWTPs) data analysis, is presented.
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Lead Distribution in Urban Soil in a Medium-Sized City: Household-Scale Analysis.
TL;DR: In this article, a combination of field sampling, statistical analysis, and machine learning techniques was used to characterize potential soil lead exposure risk at the household scale in Greensboro, North Carolina.
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Real-Time Sensor Response Characteristics of 3 Commercial Metal Oxide Sensors for Detection of BTEX and Chlorinated Aliphatic Hydrocarbon Organic Vapors
Gabriel Yurko,Javad Roostaei,Timothy M. Dittrich,Lanyu Xu,Michael Ewing,Yongli Zhang,Gina Shreve +6 more
TL;DR: In this article, the authors examined the sensor response characteristics of three commercial Internet of Things compatible metal oxide (MOx) sensors in preparation for the development of field-scale sensor networks for the real-time monitoring of volatile organic compounds (VOCs) in indoor environments located in proximity to brownfield sites.